This PDF file contains the front matter associated with SPIE Proceedings Volume 6981, including the Title Page, Copyright information, Table of Contents, Introduction, and the Conference Committee listing.

The Air Force Research Laboratory (AFRL) mission is to provide support to the Air Force (AF) and the warfighters with an understanding of the science and technology that will form the foundation of future capabilities. AFRL has developed a strategic research and development process that translates the Department of Defense future capability needs into mid-term attributes, described in terms of technology achievements. Specific capabilities, like the delivery of a close-in sensing platform, require technologies from many different disciplines and require aligning priorities for nurturing and developing core competencies. AFRL's strategic vision is built upon the AF Science & Technology (S&T) Vision of Anticipate, Find, Fix, Track, Target, Engage, and Access - Anything, Anywhere, Anytime. In order to realize this vision, AFRL has developed Focused Long Term Challenges (FLTCs) that describe the AF problem space and constitute the AFRL long term S&T planning.

As reliance upon advanced networked sensors increases, expert decision support tools (DSTs) are needed to recommend appropriate mixes of sensors and placements that will maximize their effectiveness. These tools should predict effects on sensor performance of the many complexities of the environment, such as terrain conditions, the atmospheric state, and background noise and clutter. However, the information available for such inputs is often incomplete and imprecise. To avoid drawing unwarranted conclusions from DSTs, the calculations should reflect a realistic degree of uncertainty in the inputs. In this paper, a Bayesian probabilistic framework is developed that provides sensor performance predictions given explicit uncertainties in the weather forecast, terrain state, and tactical scenario. A likelihood function for the signature propagation model parameters is specified based on the forecast and additional local information that may be supplied by the user. The framework also includes a likelihood function for the signal/noise features as a function of the propagation model parameters and tactical scenario. Example calculations illustrate the significant impact of uncertainty in optimal sensor selection and DST predictions.

This paper describes the joint US & UK International Technology Alliance (ITA) basic research programme in Network and Information Science (NIS), with a particular focus on the elements of the research programme concerned with the processing of sensor information and the delivery of sensor derived information and intelligence to the users. The paper provides a view of both the benefits and the main challenges being addressed by the NIS ITA, with a particular focus on Sensor Information Processing and Delivery (SIPD): SIPD is one of the four key thrusts within the NIS ITA.

Mobile Ad-Hoc Networks (MANETs), that do not rely on pre-existing infrastructure and that can adapt rapidly to changes in their environment, are coming into increasingly wide use in military applications. At the same time, the large computing power and memory available today even for small, mobile devices, allows us to build extremely large, sophisticated and complex networks. Such networks, however, and the software controlling them are potentially vulnerable to catastrophic failures because of their size and complexity. Biological networks have many of these same characteristics and are potentially subject to the same problems. But in successful organisms, these biological networks do in fact function well so that the organism can survive. In this paper, we present a MANET architecture developed based on a feature, called homeostasis, widely observed in biological networks but not ordinarily seen in computer networks. This feature allows the network to switch to an alternate mode of operation under stress or attack and then return to the original mode of operation after the problem has been resolved. We explore the potential benefits such an architecture has, principally in terms of the ability to survive radical changes in its environment using an illustrative example.

One of the challenges in military wireless sensor networks is the determination of an information collection infrastructure that minimizes battery power consumption while being highly resilient against sensor and link failures. In our previous work we have proposed a heuristic for constructing an information flow graph in wireless sensor networks based on the mammalian circulatory system, with the goal of minimizing the energy consumption. In this paper we focus mainly on the resilience benefits that can be achieved when constructing such information flow graphs. We analyze the resilience of circulatory graphs constructed on top of regular as well as random topologies. We assume two modes of failure, random and targeted attacks, and we compare the resilience of the circulatory graphs against tree graphs.

A light-weight messaging fabric can be used to interconnect several different types of sensors together in a light-weight manner using existing products. However, existing commercial solutions for interconnecting sensors do not provide an easy method to enforce communication flow policies among several different methods, nor do they provide an easy interface for auto-configuration of sensor flows to enforce messaging policies. In this paper, we describe an approach that can add the features of self-configuration and policy based security controls to a sensor network built atop a message queue infrastructure. We describe the architecture for providing policy control and self-configuration network management functions to the sensor messaging fabric.

Making decisions on how best to utilise limited intelligence, surveillance and reconnaisance (ISR) resources is a key issue in mission planning. This requires judgements about which kinds of available sensors are more or less appropriate for specific ISR tasks in a mission. A methodological approach to addressing this kind of decision problem in the military context is the Missions and Means Framework (MMF), which provides a structured way to analyse a mission in terms of tasks, and assess the effectiveness of various means for accomplishing those tasks. Moreover, the problem can be defined as knowledge-based matchmaking: matching the ISR requirements of tasks to the ISR-providing capabilities of available sensors. In this paper we show how the MMF can be represented formally as an ontology (that is, a specification of a conceptualisation); we also represent knowledge about ISR requirements and sensors, and then use automated reasoning to solve the matchmaking problem. We adopt the Semantic Web approach and the Web Ontology Language (OWL), allowing us to import elements of existing sensor knowledge bases. Our core ontologies use the description logic subset of OWL, providing efficient reasoning. We describe a prototype tool as a proof-of-concept for our approach. We discuss the various kinds of possible sensor-mission matches, both exact and inexact, and how the tool helps mission planners consider alternative choices of sensors.

This paper examines the practical challenges in the application of the distributed network utility maximization (NUM) framework to the problem of resource allocation and sensor device adaptation in a mission-centric wireless sensor network (WSN) environment. By providing rich (multi-modal), real-time information about a variety of (often inaccessible or hostile) operating environments, sensors such as video, acoustic and short-aperture radar enhance the situational awareness of many battlefield missions. Prior work on the applicability of the NUM framework to mission-centric WSNs has focused on tackling the challenges introduced by i) the definition of an individual mission's utility as a collective function of multiple sensor flows and ii) the dissemination of an individual sensor's data via a multicast tree to multiple consuming missions. However, the practical application and performance of this framework is influenced by several parameters internal to the framework and also by implementation-specific decisions. This is made further complex due to mobile nodes. In this paper, we use discrete-event simulations to study the effects of these parameters on the performance of the protocol in terms of speed of convergence, packet loss, and signaling overhead thereby addressing the challenges posed by wireless interference and node mobility in ad-hoc battlefield scenarios. This study provides better understanding of the issues involved in the practical adaptation of the NUM framework. It also helps identify potential avenues of improvement within the framework and protocol.

The ability of a sensor device is affected significantly by the surroundings and environment in which it is placed. In almost all sensor modalities, some directions are better observed by a sensor than others. Furthermore, the exact impact on the sensing ability of the device is dependent on the position assigned to the sensor. While the problem of determining good coverage schemes for sensors of a field have many good solutions, not many approaches are known to address the challenges arising due to location specific distortion. In this paper, we look at the problem of incorporating terrain specific challenges in sensor coverage, and propose a geometric solution to address them.

The Unmanned Autonomous Collaborative Operations (UACO) program was initiated in recognition of the high operational burden associated with utilizing unmanned systems by both mounted and dismounted, ground and airborne warfighters. The program was previously introduced at the 62nd Annual Forum of the American Helicopter Society in May of 20061. This paper presents the three technical approaches taken and results obtained in UACO. All three approaches were validated extensively in contractor simulations, two were validated in government simulation, one was flight tested outside the UACO program, and one was flight tested in Part 2 of UACO. Results and recommendations are discussed regarding diverse areas such as user training and human-machine interface, workload distribution, UAV flight safety, data link bandwidth, user interface constructs, adaptive algorithms, air vehicle system integration, and target recognition. Finally, a vision for UAV As A Wingman is presented.

We address architectural and design considerations to a service-oriented architecture designed for the tactical environment. This architecture, dubbed tactical service-oriented architecture, must be responsive to changing network conditions and the quick addition or removal of network-enabled nodes. It must be supportive of a variety of heterogeneous data networks and support translation of data between incompatible networks and systems. Additionally, it will need to support the various operating environments of tactical edge assets. The architecture and design considerations asserted in this paper are backed by lab test bed development, cooperative research with industry and government labs, participation with relevant working groups, and participation in real-world exercises utilizing airborne networks.

Increased vehicle autonomy, survivability and utility can provide an unprecedented impact on mission success and are one of the most desirable improvements for modern autonomous vehicles. We propose a general architecture of intelligent resource allocation, reconfigurable control and system restructuring for autonomous vehicles. The architecture is based on fault-tolerant control and lifetime prediction principles, and it provides improved vehicle survivability, extended service intervals, greater operational autonomy through lower rate of time-critical mission failures and lesser dependence on supplies and maintenance. The architecture enables mission distribution, adaptation and execution constrained on vehicle and payload faults and desirable lifetime. The proposed architecture will allow managing missions more efficiently by weighing vehicle capabilities versus mission objectives and replacing the vehicle only when it is necessary.

In airborne UAV operations, it is desirable to havemultiple UAVs operate in a cooperationmode tomaximize the use of resources, as well as take unique advantages of increased views frommultiple positions separated in time and space. This capability requires image registration across potentially widely different views that are taken at different places or time. The resulting images also vary in their noise contents, resolutions, and projection deformation. In this paper, we characterize the performance enhancement between single view from a single UAV and multiple views by multiple UAVs using ROC curves. In addition, we propose a computational framework to facilitate an efficient and accurate registration across images with varied resolutions, noise levels, and projective deformation. We implement various stages in this framework and demonstrate the promising results using low to medium resolution images with synthetically-generated flying path and camera poses.

Finding, tracking and monitoring events and activities of interest on a continuous basis remains one of our highest Intelligence Surveillance and Reconnaissance (ISR) requirements. Unmanned Aerial Systems (UAS) serve as one of the warfighter's primary and most responsive means for surveillance and gathering intelligence information and are becoming vital assets in military operations. This is demonstrated by their significant use in Afghanistan during Operation Enduring Freedom and in Iraq as part of Operation Iraqi Freedom. Lessons learned from these operations indicate that UAVs provide critical capabilities for enhancing situational awareness, intelligence gathering and force protection for our military forces. Current UAS high resolution electro-optics offers a small high resolution field of view (FOV). This narrow FOV is a limiting factor on the utility of the EO system. The UAS that are available offer persistence; however, the effectiveness of the EO system is limited by the sensors and available processing. DARPA is addressing this developing the next generation of persistent, very wide area surveillance with the Autonomous Real-time Ground Ubiquitous Surveillance - Imaging System (ARGUS-IS). The system will be capable of imaging an area of greater than 40 square kilometers with a Ground Space Distance (GSD) of 15 cm at video rates of greater than 12 Hz. This paper will discuss the elements of the ARGUS-IS program.

An alternative to conventional techniques for compressing video data of moving objects is described. The method, known as track-based compression (TBC), detects, associates, and tracks moving objects between frames, sending only a small chip or ID around the moving object once the track has been established. The compression ratio achievable depends on scene content, sensor geometry, the degree to which the background can be stabilized, and other factors. Preliminary results range from 1,500:1 for oblique sensing geometries with significant parallax to more than 10,000:1 for near-nadir overhead and fixed ground-based surveillance video.

The focus of this paper is on the exploitation of new staring sensors to address the urban surveillance challenge and help combat the war on terror. A staring sensor visualization environment, known as the Data Table, will be presented which integrates staring sensors with close-in sensors, such as small UAVs, building mounted sensors, and unattended ground sensors (UGS). There are several staring sensors in development, but two in particular will be highlighted in this paper - NightStare and the Gotcha Radar, both under development by the Air Force Research Laboratory (AFRL).

The Secure Border Initiative Network (SBInet) is a series of sensor platforms along the U.S. border areas for the purpose of better monitoring cross-border excursions. From a technical standpoint, the challenge of SBInet is to provide the necessary area coverage needed while controlling costs. This paper presents one set of methods for analyzing different tower locations and technologies. Since the purpose of the paper is to consider analytical techniques, the terrain and tower locations used do not relate to the P28 area nor any other specific approaches or tower locations currently being studied for the SBInet program.

Net-Centric Warfare, in all of its forms, revolves around the Internet Protocol suite, using it as the foundation for data transfers. We briefly examine the origins of the Internet Protocol and its design philosophies, as well as the problems this design causes military tactical data systems and radio links. The DARPA Control Plane program's goal was to solve some of these problems; the program's work is covered in sections two and three. An important lesson from the Control Plane program is the ability to maintain much more knowledge, or "state," about networks than was previously thought possible. Given the new ability to maintain more state about both the network and the connections within the network, it is possible to manage military networks in a more controlled fashion than we have in the past. The last two sections of the paper explore a possible approach for more controlled and manageable networks, as well as some of the potential benefits.

In this paper we introduce a cross-layer mechanism to enhance the effectiveness of link-state routing protocols by providing a localized estimate of the validity of a given route. Accurate predictions of route staleness result in less packet loss by selecting alternative paths before primary path failures. We present a proof of concept implementation that utilizes shared location and velocity information provided from each node through a common cross-layer substrate. Simulations using random-walk mobility models are presented for the OLSR protocol. The results show that predictive route adaptation can significantly reduce the average packet loss, average delay and jitter.

Forces engaged in tactical urban combat operations require a continuous and comprehensive picture of the combat environment to quickly detect the target and effectively reduce opposition. This requires a significant coordination of actions, situational awareness, and fast decision-making. This paper focuses on modeling the collaboration acts among multiple combat units. We analyze the tactics of urban combat operations and then propose a general framework for modeling collaboration among units. Our approach uses Multi-Agent Systems (MAS) as a paradigm for modeling Command and Control (C2) in urban combat operations. We introduce the notion of scenario-based and policy-based MAS collaboration, and analyze different MAS inter-agent structural and control architectures, including hierarchical and federated architectures. This paper shows how scenario-based and policy-based collaboration matched with different MAS control architectures fits the C2 requirements of urban combat operations.

Tactical net-centric systems must support the exchange of multi-media information among traditional and non-traditional partners in a highly complex and dynamic environment across the full spectrum of operations. These systems also need to support the establishment of both static and dynamic groups of users able to get the right information, to the right person, at the right time, with adequate information assurance - all without compromising the ability of others to use the limited network resources to do the same. We refer to these dynamic groups of users as Communities of Interest (CoIs). CoIs provide a conceptual framework in which these capabilities can be implemented whilst ensuring usability, agility, security and an overall management approach that abstracts away the complexities and challenges of the operational environment. This paper introduces several system technologies in the areas of networking, security and information management and puts them into an evolutionary system context that realizes maximum returns on investments, facilitating the achievement of net-centricity in the tactical environment.

A flexible, ubiquitous, and universal solution for management of distributed dynamic systems will be presented. It allows us to grasp complex systems at a higher than usual, semantic level, penetrating their infrastructures (also creating or modifying them) while establishing local and global dominance over any system organizations and coordinating their behavior in the way needed. The approach may allow the navigated systems to maintain high runtime integrity and automatically recover from indiscriminate damages, preserving global goal orientation and situation awareness in unpredictable and hostile environments.